Identifying disease sensitive and quantitative trait-relevant biomarkers from multidimensional heterogeneous imaging genetics data via sparse multimodal multitask learning

Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort

(2011) Hua Wang et al.   BIOINFORMATICS

Alzheimer's Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans

(2010) Andrew J. Saykin et al.   Alzheimers & Dementia

L2-norm multiple kernel learning and its application to biomedical data fusion

(2010) Shi Yu et al.   BMC BIOINFORMATICS

Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort

(2010) Li Shen et al.   NEUROIMAGE

Predicting clinical scores from magnetic resonance scans in Alzheimer's disease

(2010) Cynthia M. Stonnington et al.   NEUROIMAGE

Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset

(2009) Chris Hinrichs et al.   NEUROIMAGE

A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

(2009) Amir Beck et al.   SIAM Journal on Imaging Sciences

Joint covariate selection and joint subspace selection for multiple classification problems

(2009) Guillaume Obozinski et al.   STATISTICS AND COMPUTING

Convex multi-task feature learning

(2008) Andreas Argyriou et al.   MACHINE LEARNING

Multi-modal imaging predicts memory performance in normal aging and cognitive decline

(2008) K.B. Walhovd et al.   NEUROBIOLOGY OF AGING

Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline

(2007) Yong Fan et al.   NEUROIMAGE